hi, thanks in advance. if I want to compare the gene difference between sample in TCGA, one group has 2 samples, another groups has 78 samples, can I do RNA-seq differential Analysis? if it ok, which pakcage is better and the Minimum is what?
if not, can there be a reason
The minimum is n=1 vs n=2, same for all three packages. That's not a recommendation, just the mathematical minimum that allows a normal statistical analysis.
You will have to make your own choice between the packages, or read 3rd party comparisons in the literature. All three have very strong user bases and are capable of doing the analysis.
Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
version 2.3.6
thanks a lot you mean n=1 is the control group, n=2 in the treat group?
I have another question, I use deseq2 to do analysis, and find the significant differential genes not have a good distinction in the heatmap, I tried the vst , rlog (dds), normalized_counts <- counts(dds, normalized=TRUE) , but neither showed a good comparision in the hatmap, do you know how to solve this?
abother question is that after doing differential analysis, If I want to plot the difference of just one gene, for example, EGFR expression difference in treat and control group, can I use vst , rlog (dds), normalized_counts <- counts(dds, normalized=TRUE), most literature seems using TPM, but counts is not easy to be transformed to TPM?
about vst , rlog (dds), normalized_counts <- counts(dds, normalized=TRUE) , I know vst and rlog has some speed difference, but I know nothing elseļ¼ can you elaborate on it?
If you have a specific question about one package, make a new post and only tag that package. When you post and tag all three packages you are sending automatic notifications to all these developers to read your message. So be mindful of that in posting.
thanks a lot, I am so sorry for my rudeness